orange3

library3.40.0pypypi✓ verified 83d ago

Orange3 is a component-based data mining framework for Python, offering visual programming and a rich set of widgets for data preprocessing, modeling, and evaluation. The current stable version is 3.40.0, with a release cadence of approximately 2-3 minor versions per year.

data ai-ml

pip install orange3

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · ORANGE3

orange3

datapythonv3.40.0

harness data pending

Install & Compatibility

Where this runs

No compatibility data collected yet for this library.

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Orange.data.Table

✓ from Orange.data import Table

✗ import Orange; Orange.data.Table

Direct import is idiomatic; avoid importing the top-level Orange module and then accessing submodules.

Orange.preprocess

✓ from Orange.preprocess import Normalize, Continuize, Impute

✗ import Orange.preprocess; p = Orange.preprocess.Normalize()

Submodule imports are clearer and avoid long chained accesses.

Orange.evaluation

✓ from Orange.evaluation import CrossValidation, scoring

✗ import Orange.evaluation.CrossValidation

CrossValidation is a class in orange.evaluation module, not a submodule.

Loads the Iris dataset, normalizes features, trains a Random Forest, and evaluates with 5-fold cross-validation.

from Orange.data import Table from Orange.preprocess import Normalize from Orange.classification import RandomForestLearner from Orange.evaluation import CrossValidation, scoring # Load dataset (automatically downloads if not present) data = Table('iris') # Preprocess: normalize features normalizer = Normalize() data_norm = normalizer(data) # Train a random forest model learner = RandomForestLearner(n_estimators=50, random_state=42) # Cross-validation results = CrossValidation(data_norm, [learner], k=5) print('CA:', scoring.CA(results)[0])

orange-canvas --version

Debug

Known issues

breakingOrange3 requires Python >=3.11 as of version 3.40.0. Python 3.10 or earlier will fail to install.

fix

Upgrade Python to 3.11+.

affects: >=3.40.0

gotchaOn Windows, pip install orange3 may fail due to missing Qt DLLs. Conda install (conda-forge) is strongly recommended.

fix

Use: conda install -c conda-forge orange3

affects: all

gotchaLoading datasets with Table('dataset_name') will automatically download the dataset to ~/Orange/datasets if not present. This can cause silent network access in production environments.

fix

Manually download datasets and use local file paths: Table('/path/to/data.tab')

affects: all

deprecatedOrange.classification.SimpleRandomForestLearner is deprecated as of 3.33. Use RandomForestLearner (wraps sklearn's RandomForestClassifier).

fix

Replace SimpleRandomForestLearner with RandomForestLearner.

affects: >=3.33

Errors

Common errors & fixes

ImportError: cannot import name 'Table' from 'Orange.data'

Typo or outdated Orange version; Table is in Orange.data since Orange 3.x. In Orange 2.x it was Orange.OrangeTable.

fix

Ensure you have orange3 (not orange) installed: pip install orange3 and use 'from Orange.data import Table'.

ModuleNotFoundError: No module named 'PyQt5'

Orange3 GUI requires PyQt5; missing on some headless Linux systems or Python installations without Qt.

fix

Install PyQt5: pip install PyQt5 or use conda: conda install pyqt. Alternatively, set environment variable DISPLAY if using GUI.

Upgrade

Version history

3.40.0latest on PyPI · released Dec 20, 2025

Audit

Dependencies

numpyrequiredCore numerical dependency

scipyrequiredScientific computing

scikit-learnrequiredMachine learning algorithms

PyQt5requiredGUI framework (automatically installed on Linux/macOS, may conflict on Windows if preinstalled)

Agent activity

2 hits · last 30 days

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Resources

githubhttps://github.com/sponsors/biolab ↗

packagehttps://pypi.org/project/orange3/ ↗

homepagehttps://orangedatamining.com/ ↗

docshttps://orangedatamining.com/docs ↗